Abstract
Abstract Mapping of the spatial variability of sparse groundwater-level measurements is usually achieved by means of geostatistical methods. This work tackles the problem of deficient sampling of an aquifer, by employing an innovative integer adaptive genetic algorithm (iaGA) coupled with geostatistical modelling by means of ordinary kriging, to optimise the monitoring network. Fitness functions based on three different errors are used for removing a constant number of boreholes from the monitoring network. The developed methodology has been applied to the Mires basin in Crete, Greece. The methodological improvement proposed concerns the adaptive method for the GA, which affects the crossover–mutation fractions depending on the stall parameter, aiming at higher accuracy and faster convergence of the GA. The initial dataset consists of 70 monitoring boreholes and the applied methodology shows that as many as 40 boreholes can be removed, while still retaining an accurate mapping of groundwater levels. The proposed scenario for optimising the monitoring network consists of removing 30 boreholes, in which case the estimated uncertainty is considerably smaller. A sensitivity analysis is conducted to compare the performance of the standard GA with the proposed iaGA. The integrated methodology presented is easily replicable for other areas for efficient monitoring networks design.
Highlights
Protecting water resources is part of the sixth goal of the United Nations proposed to transform our world in order to promote prosperity while protecting the planet (United Nations 2018)
We have not focused on a detailed investigation of semivariogram calculation for the initial groundwater-level data mapping, as this is scrutinised in the cited work
The OK interpolation results regarding the initial dataset by means of the Spartan and power-law variograms are presented in Figures 5 and 6
Summary
Protecting water resources is part of the sixth goal of the United Nations proposed to transform our world in order to promote prosperity while protecting the planet (United Nations 2018). Groundwater monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Data from such networks are typically used by competent authorities and scientists to validate groundwater flow and contaminant transport models, to assess the response of groundwater levels to pumping, artificial recharge and changing climatic variables and to regulate groundwater exploitation to ensure the sustainability of aquifer resources. The design of a groundwater monitoring network depends on the spatial and temporal distribution of water levels in the aquifer and the location of potential contaminant sources. For long-term monitoring of water levels, the typical objective is the development of a cost-effective network that retains the monitoring boreholes, which contribute to the accurate representation of the spatial variability of the aquifer’s groundwater level and excludes boreholes that add little or no beneficial
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